Electronic signal processing will usually induce some level of noise into the output signal. In the transmission of signals, the induced noise is often due to ‘lossy’ transmission methods. Ordinary workers in this field will understand that ‘lossy’ refers to processing techniques that move some signal data to nearby data values.
Lossy signal compression techniques make transmission quicker and more efficient but introduce noise when the transmitted signal is compressed. This level of noise can be controlled and restricted to an acceptable level for the vast majority of the transmission. However, there are instances where the signal data at one or more particulars levels within the bandwidth are more important than others. Alternatively, noise at particular levels of the bandwidth has a more detrimental effect than it would at other levels of the bandwidth. The aggressiveness of the compression technique can be set so that the noise in these critical sections is acceptable, but then majority of the bandwidth is only lightly compressed and the data size remains large. Keeping the data size large tends to defeat the purpose of compressing the signal in the first place.
JPEG (Joint Photographic Experts Group) compression of contone image data is one example of a lossy signal compression technique. The noise induced by JPEG compression in particular sections of the bandwidth can cause particularly visible artifacts in the decompressed image. Because of its relevance to the present invention, the detailed description is directed to localized noise reduction in the compression and decompression of an image file. However, it will be appreciated that this is purely illustrative and the invention encompasses other types of signal transmission.
JPEG compression of image data uses one of a suite of standard algorithms to reduce data size for faster transmission and more efficient storage. The quality of the resultant image is determined by the level of compression. An aggressive compression greatly reduces the file size but introduces high levels of noise. Light compression reduces the noise but the data size remains relatively large. Therefore, the optimum level of compression is a trade off between image quality and data size, having regard to the characteristics of the output device (printer or monitor), processing capabilities and resolution requirements.
During JPEG compression, the image is analyzed in blocks of 8×8 pixels. Depending on the level of compression selected, the detail in each of the blocks is reduced. In more aggressive compressions, the 8×8 blocks can become visible in the final image. The compression should be at a level where the noise in the resulting image is imperceptible. Unfortunately, there are often certain components of an image that are far more prone to decompression artifacts than the rest of the image. In these cases, the noise is imperceptible for the majority of the image, but produces artifacts in certain parts.
The noise prone areas are hard edges between strongly contrasting colors such as text on a white background. FIG. 1 is an image of a black shape 10 on a white background 12 without any noise. FIG. 2 shows the associated grayscale histogram for the image. The histogram has 256 levels, with level 0 being white and level 255 being black. A black shape on a white background (without any noise) has pixels in levels 0 or 255 only. All other levels are shades of grey and therefore empty.
FIG. 3 shows the image of FIG. 1 after it has been JPEG compressed and decompressed. The detail lost during compression manifests as random grey scale artifacts 14 around the periphery of the black shape 10. The grey scale artifacts also exist within the black shape 10 but are obscured by the surrounding black. The artifacts 14 are confined to the 8×8 pixel blocks that cross the boundary between the shape and the white background. These artifacts are referred to as JPEG ‘ringing’.
FIG. 4 shows the histogram for FIG. 3. While most of the pixels are in level 0 or 255 (white or black), the noise appears in the levels near the two extremities 16 and 18. The noise is restricted to the ends of the histogram because compression tends to cause only small shifts in a pixels color level. In a ‘normal’ photographic image, most if not all of the intensity levels in each colour plane have some pixels. The noise from compression does not shift the colour levels very far from the original level, and mixes with the other color planes, so the artifacts occur at a high spatial frequency. The eye is insensitive to high frequency noise made up of small colour levels shifts. It is only the sharp edges between strongly contrasting colors where the artifacts become visible.